There are several techniques for controlling devices using gestures. The most possibilities for controlling devices using gestures are afforded by those techniques that allow for remotely capturing a three-dimensional (3D) image of the person making a gesture with his head, face, eyes, hands, and/or legs, as well as remotely capturing a 3D image of different changes in the posture of the user that can be interpreted as gestures.
However, most present solutions for controlling devices using gestures have rather limited capabilities as far as the processing power and resolution of these devices' 3D image-capturing systems are concerned. In most instances, this results in the inability of these systems to detect minor gestures (gestures made by the smaller body parts of the user) and perform face recognition.
In addition to the afore-mentioned limitations, the present solutions typically fail to distinguish between the casual gestures of the user and those gestures that are made meaningfully and are, thus, actionable. This makes the user spend some time on preparing for making a gesture, thereby significantly inconveniencing the user.
In addition, the limited capturing ability of the present solutions necessitates some preliminary training on behalf of the user in order to be able to operate the 3D sensor device, limits the user in the speed of gesturing, and makes him or her use only those gestures that are simple, emphasized, slow, easily recognizable, and reliably distinguishable from one another.
The above significant functional limitations detract severely from the user experience, while considerably confining the scope of application of the 3D sensor.